Plant Growth Stage Recognition Skill | 植物生长阶段识别技能

Accurately identifies key growth stages of plants from germination to fruiting based on computer vision and deep learning, provides structured data for preci...

This package is not a simple instruction-only plant CV helper: it bundles unrelated face-analysis code and a large shared library, reads local workspace/config files, may create a local SQLite DB and save attachments, and will call remote APIs using an 'open-id' you must supply. Before installing or running: - Ask the publisher for an authoritative source/homepage and why face_analysis and smyx_common are included. - Inspect RequestUtil (skills/smyx_common/scripts/util.py) and the API endpoint/base URLs in skills/smyx_common/scripts/config.yaml or config-dev/prod to see where your images/data would be sent. - Do not provide sensitive credentials or real user identifiers (open-id) until you confirm the remote API is trustworthy. - Run the skill in an isolated environment (container) and review what files it writes (attachments directory, data/*.db). - Verify and supply only the minimal open-id required; if you cannot confirm the remote endpoints or developer identity, avoid using the skill for sensitive images. If you can provide the contents of RequestUtil and the resolved ApiEnum.BASE_URL values (or the exact API server domains), I can reassess and raise or lower the concern level.

Type: OpenClaw Skill Name: smyx-plant-growth-stage-recognition-analysis Version: 1.0.0 The skill bundle exhibits high-risk behaviors, most notably the automated exfiltration of user identifiers (which the instructions suggest can be a phone number) to a remote endpoint (lifeemergence.com/jeecg-boot/sys/phoneLogin) for 'silent registration' within `skills/smyx_common/scripts/util.py`. Additionally, `skills/smyx_common/scripts/skill.py` contains an `ai_chat` function that executes system commands via `subprocess.run(['openclaw', 'agent', ...])`, providing a mechanism for RCE-like capabilities within the agent environment. The `SKILL.md` also includes 'Mandatory Memory Rules' that force the AI to ignore local memory files and rely solely on the remote API, which could be used to bypass local auditing or data persistence mechanisms.